Integrated Proteome/Transcriptome Profiling of Tomato Fruit

We are integrating a tomato fruit
transcript expression profiling initiative with the cell wall
proteome analysis, in both wild type ripening fruit and those of the
ripening impaired mutants ripening inhibitor (rin), non-ripening (Nor)
and never ripe (Nr). The transcriptome data is being generated with
the 8,700 unigene TOM1 cDNA array, the long oligonucleotide 12,000
unigene (TOM2) microarrays and two RNASeq platforms (454 and
Illumina).

Following the identification of genes and their cognate proteins
through comparison of MS-derived protein sequence analysis with the
complement of the tomato microarray, microarray and proteomics data of
this gene set are directly compared to identify: (a) genes showing
significant expression changes by proteomic analysis but not by
microarray analysis, or vice versa, through fruit development, or in
comparison with mutant fruits; (b) genes showing significant
differences between changes in transcript and cognate protein levels.

Objectives

Compare the protein and transcriptome profile of each gene in the
groups above using correlation analysis and define three different
categories: those showing positive, negative or no significant
correlation between microarray and proteomic analysis.

If data sets of sufficient size result, the number of genes
represented in each group will be used to derive estimates of
secretome genes under transcriptional and/or post-transcriptional
control.

Classify the genes into different functional categories to determine
whether certain classes of secretome genes are primarily under
transcriptional and/or post-transcriptional control during ripening.

Most studies of the biochemical and regulatory pathways that are
associated with, and control, fruit expansion and ripening are based
on homogenized bulk tissues, and do not take into consideration the
multiplicity of different cell types from which the analytes
(transcripts, proteins or metabolites) are extracted. Consequently,
potentially valuable spatial information is lost and the lower
abundance cellular components that are expressed only in certain cell
types can be diluted below the level of detection.

We are using laser capture microdissection (LMD), coupled with
transcript profiling using RNAseq to identify tissue type specific
transcripts and molecular pathways, in to gain new insights into
aspects of tissue-specific gene expression, and consequently tissue
and organ physiology. In this regard, we are particularly interested
in defining tissue-specific secretomes. In addition, this deeper
mining of the transcriptome is extremely valuable for tomato gene
annotation; for example, revealing substantial alternative splicing,
which in turn is critical for enhancing the proteome analyses.

Tomato fruit pericarp section after removal of the vascular tissue using LMD.

Objectives

Construct and sequence tissue specific transcript libraries for
each tissue in tomato fruit pericarp, using 454 and Illumina
technologies , at various developmental stages

Characterize the predicted secretomes of each tissue

Use the deep coverage of the transcripts to identify enhance gene
space definition, and therefore peptide matching for the proteomic
studies

To date, a total of 1,456,024 high quality sequences have been
generated, distributed among the tissue libraries. Following sequence
assembly, 20,976 tomato unigenes (assembled from at least five reads)
were associated with one or more of the tissues.